function [Train Test] = plotData()
    Banana = load('banana.mat');

    [Train Test] = combineSets(Banana, 0.75, 20);
    
    %plotting the test and training set
    Aplot = Train(find(Train(:,3)),1:2);
    Bplot = Train(find(Train(:,4)),1:2);    
    plot(Aplot(:,1),Aplot(:,2),'.',Bplot(:,1),Bplot(:,2),'*');
    legend('training data A', 'training data B');
    %xlim([-15 15]);
    
   % Maybe we can use this later: 
   %  waitforbuttonpress;
   % %test different k's 
   % for k=1:100,
   %     classifier = knn(2,2, k, Train(:,1:2), Train(:,3:4));
   %     [Results Labels] = knnfwd(classifier,Test(:,1:2));
   %     mat = confmat(Results, Test(:,3:4));
   %     correct(k) = (mat(1,1) + mat(2,2)) / length(Results);
   %     false(k) = 1-correct(k);
   % end
   % 
   % %plot the error rate over different k's
   % plot([1:100], false);
   % xlabel('k');
   % ylabel('error value');
end
